Data Governance Workflows & Stewardship
Automated data governance processes with stewardship workflows, change approval, and audit trails for enterprise data quality.
Why This Matters
What It Is
Automated data governance processes with stewardship workflows, change approval, and audit trails for enterprise data quality.
Current State vs Future State Comparison
Current State
(Traditional)Ad-hoc data governance with informal processes and email-based change requests. No clear data ownership or stewardship roles. Data changes made directly in source systems without approval workflows or audit trails. Limited visibility into who changed what data and when. Reactive data quality management when issues surface.
Characteristics
- • MDM Platforms (e.g., Informatica MDM, SAP Master Data Governance)
- • Data Catalogs (e.g., Alation, Collibra)
- • ETL/ELT Solutions (e.g., Talend, Apache NiFi)
- • Enterprise Systems (e.g., Salesforce, SAP ERP)
- • Traditional Tools (e.g., Microsoft Excel, Email)
- • Microsoft Purview
Pain Points
- ⚠ Data Quality Issues: Persistent errors across source systems requiring ongoing root cause analysis.
- ⚠ Fragmented Data Sources: Complexity in managing master data across multiple systems without a unified view.
- ⚠ Organizational Alignment: Challenges in establishing clear roles and responsibilities across departments.
- ⚠ Process Obsolescence: Difficulty in maintaining up-to-date data policies as business needs evolve.
- ⚠ Scalability Constraints: Challenges in expanding pilot programs across multiple data domains while ensuring integration.
Future State
(Agentic)AI-powered data governance platform orchestrates end-to-end data stewardship workflows with role-based approval hierarchies. Machine learning automatically routes data change requests to appropriate data stewards based on data domain, criticality, and scope of change. Automated data quality validation pre-approves low-risk changes (e.g., adding missing email address) while flagging high-risk changes (e.g., merging customer records, changing product category) for human review. Complete audit trail captures all data changes with user identity, timestamp, before/after values, and business justification. AI-generated data lineage diagrams show impact of proposed changes across downstream systems. Predictive analytics identify data quality trends and recommend proactive stewardship actions. Workflow SLAs with automated escalations prevent bottlenecks.
Characteristics
- • Master data change requests
- • Data ownership and stewardship roles (RACI)
- • Data quality rules and validation logic
- • Data lineage and system dependencies
- • Historical change audit logs
- • Workflow SLA definitions
Benefits
- ✓ 100% data change approval coverage (vs informal/ad-hoc)
- ✓ Complete audit trail for all master data changes
- ✓ 70-85% reduction in data governance cycle time through automation
- ✓ 50-70% of low-risk changes auto-approved (vs 0%)
- ✓ Improved data governance maturity (Level 4-5)
Is This Right for You?
This score is based on general applicability (industry fit, implementation complexity, and ROI potential). Use the Preferences button above to set your industry, role, and company profile for personalized matching.
Why this score:
- • Applicable across multiple industries
- • Higher complexity - requires more resources and planning
- • Moderate expected business value
- • Time to value: 3-6 months
- • (Score based on general applicability - set preferences for personalized matching)
You might benefit from Data Governance Workflows & Stewardship if:
- You're experiencing: Data Quality Issues: Persistent errors across source systems requiring ongoing root cause analysis.
- You're experiencing: Fragmented Data Sources: Complexity in managing master data across multiple systems without a unified view.
- You're experiencing: Organizational Alignment: Challenges in establishing clear roles and responsibilities across departments.
This may not be right for you if:
- High implementation complexity - ensure adequate technical resources
- Requires human oversight for critical decision points - not fully autonomous
Parent Capability
Data Governance & Privacy
Enterprise data governance with privacy compliance automation and consent management achieving high regulatory compliance and significant reduction in privacy violations.
What to Do Next
Related Functions
Metadata
- Function ID
- function-mdm-data-governance-workflows